def get_shape(kind='line',x=None,y=None,x0=None,y0=None,x1=None,y1=None,span=0,color='red',dash='solid',width=1,
fillcolor=None,fill=False,opacity=1,xref='x',yref='y'):
"""
Returns a plotly shape
Parameters:
-----------
kind : string
Shape kind
line
rect
circle
x : float
x values for the shape.
This assumes x0=x1
x0 : float
x0 value for the shape
x1 : float
x1 value for the shape
y : float
y values for the shape.
This assumes y0=y1
y0 : float
y0 value for the shape
y1 : float
y1 value for the shape
color : string
color for shape line
dash : string
line style
solid
dash
dashdot
dot
width : int
line width
fillcolor : string
shape fill color
fill : bool
If True then fill shape
If not fillcolor then the
line color will be used
opacity : float [0,1]
opacity of the fill
xref : string
Sets the x coordinate system
which this object refers to
'x'
'paper'
'x2' etc
yref : string
Sets the y coordinate system
which this object refers to
'y'
'paper'
'y2' etc
"""
if not x1:
if not x0:
if not x:
xref='paper'
x0=0
x1=1
else:
x0=x1=x
else:
x1=x0
if not y1:
if not y0:
if not y:
yref='paper'
y0=0
y1=1
else:
y0=y1=y
else:
y1=y0
shape = { 'x0':x0,
'y0':y0,
'x1':x1,
'y1':y1,
'line' : {
'color':normalize(color),
'width':width,
'dash':dash
},
'xref':xref,
'yref':yref
}
if kind=='line':
shape['type']='line'
elif kind=='circle':
shape['type']='circle'
elif kind=='rect':
shape['type']='rect'
else:
raise Exception("Invalid or unkown shape type : {0}".format(kind))
if (fill or fillcolor) and kind!='line':
fillcolor = color if not fillcolor else fillcolor
fillcolor=to_rgba(normalize(fillcolor),opacity)
shape['fillcolor']=fillcolor
return shape
def _to_iplot(self,
colors=None,
colorscale=None,
kind='scatter',
mode='lines',
symbol='dot',
size='12',
fill=False,
width=3,
sortbars=False,
keys=False,
bestfit=False,
bestfit_colors=None,
asDates=False,
**kwargs):
"""
Generates a plotly Data object
Parameters
----------
colors : list or dict
{key:color} to specify the color for each column
[colors] to use the colors in the defined order
colorscale : str
Color scale name
Only valid if 'colors' is null
See cufflinks.colors.scales() for available scales
kind : string
Kind of chart
scatter
bar
mode : string
Plotting mode for scatter trace
lines
markers
lines+markers
lines+text
markers+text
lines+markers+text
symbol : string
The symbol that is drawn on the plot for each marker
Valid only when mode includes markers
dot
cross
diamond
square
triangle-down
triangle-left
triangle-right
triangle-up
x
size : string or int
Size of marker
Valid only if marker in mode
fill : bool
Filled Traces
width : int
Line width
sortbars : bool
Sort bars in descending order
* Only valid when kind='bar'
keys : list of columns
List of columns to chart.
Also can be usded for custom sorting.
bestfit : boolean or list
If True then a best fit line will be generated for
all columns.
If list then a best fit line will be generated for
each key on the list.
bestfit_colors : list or dict
{key:color} to specify the color for each column
[colors] to use the colors in the defined order
asDates : bool
If true it forces truncates times from a DatetimeIndex
"""
df = self.copy()
if df.index.__class__.__name__ in ('PeriodIndex', 'DatetimeIndex'):
if asDates:
df.index = df.index.date
x = df.index.format()
else:
x = df.index.values
lines = {}
if type(df) == pd.core.series.Series:
df = pd.DataFrame({df.name: df})
if not keys:
if 'bar' in kind:
if sortbars:
keys = df.sum().sort(inplace=False, ascending=False).keys()
else:
keys = df.keys()
else:
keys = df.keys()
colors = get_colors(colors, colorscale, keys)
for key in keys:
lines[key] = {}
lines[key]["x"] = x
lines[key]["y"] = df[key].fillna('').values
lines[key]["name"] = key
if 'bar' in kind:
lines[key]["marker"] = {
'color': to_rgba(colors[key], .6),
'line': {
'color': colors[key],
'width': 1
}
}
else:
lines[key]["line"] = {'color': colors[key], 'width': width}
lines[key]["mode"] = mode
if 'marker' in mode:
lines[key]["marker"] = Marker(symbol=symbol, size=size)
if fill:
lines[key]["fill"] = 'tonexty' if kind == 'area' else 'tozeroy'
lines[key]["fillcolor"] = to_rgba(
colors[key],
kwargs['opacity'] if 'opacity' in kwargs else .3)
if 'bar' in kind:
lines_plotly = [Bar(lines[key]) for key in keys]
else:
lines_plotly = [Scatter(lines[key]) for key in keys]
for trace in lines_plotly:
if isinstance(trace['name'], pd.tslib.Timestamp):
trace.update(name=str(trace['name']))
if bestfit:
if type(bestfit) == list:
keys = bestfit
d = {}
for key in keys:
bestfit = df[key].bestfit()
d[bestfit.formula] = bestfit
bestfit_lines = pd.DataFrame(d).to_iplot(bestfit=False,
colors=bestfit_colors,
kind='scatter')
for line in bestfit_lines:
line['line']['dash'] = 'dash'
if not bestfit_colors:
line['line']['color'] = to_rgba(line['line']['color'], .6)
data = Data(lines_plotly)
data.extend(bestfit_lines)
return data
return Data(lines_plotly)
def _to_iplot(self,colors=None,colorscale=None,kind='scatter',mode='lines',symbol='dot',size='12',fill=False,
width=3,sortbars=False,keys=False,bestfit=False,bestfit_colors=None,asDates=False,**kwargs):
"""
Generates a plotly Data object
Parameters
----------
colors : list or dict
{key:color} to specify the color for each column
[colors] to use the colors in the defined order
colorscale : str
Color scale name
Only valid if 'colors' is null
See cufflinks.colors.scales() for available scales
kind : string
Kind of chart
scatter
bar
mode : string
Plotting mode for scatter trace
lines
markers
lines+markers
lines+text
markers+text
lines+markers+text
symbol : string
The symbol that is drawn on the plot for each marker
Valid only when mode includes markers
dot
cross
diamond
square
triangle-down
triangle-left
triangle-right
triangle-up
x
size : string or int
Size of marker
Valid only if marker in mode
fill : bool
Filled Traces
width : int
Line width
sortbars : bool
Sort bars in descending order
* Only valid when kind='bar'
keys : list of columns
List of columns to chart.
Also can be usded for custom sorting.
bestfit : boolean or list
If True then a best fit line will be generated for
all columns.
If list then a best fit line will be generated for
each key on the list.
bestfit_colors : list or dict
{key:color} to specify the color for each column
[colors] to use the colors in the defined order
asDates : bool
If true it forces truncates times from a DatetimeIndex
"""
df=self.copy()
if df.index.__class__.__name__ in ('PeriodIndex','DatetimeIndex'):
if asDates:
df.index=df.index.date
x=df.index.format()
else:
x = df.index.values
lines={}
if type(df)==pd.core.series.Series:
df=pd.DataFrame({df.name:df})
if not keys:
if 'bar' in kind:
if sortbars:
keys=df.sum().sort(inplace=False,ascending=False).keys()
else:
keys=df.keys()
else:
keys=df.keys()
colors=get_colors(colors,colorscale,keys)
for key in keys:
lines[key]={}
lines[key]["x"]=x
lines[key]["y"]=df[key].fillna('').values
lines[key]["name"]=key
if 'bar' in kind:
lines[key]["marker"]={'color':to_rgba(colors[key],.6),'line':{'color':colors[key],'width':1}}
else:
lines[key]["line"]={'color':colors[key],'width':width}
lines[key]["mode"]=mode
if 'marker' in mode:
lines[key]["marker"]=Marker(symbol=symbol,size=size)
if fill:
lines[key]["fill"]='tonexty' if kind=='area' else 'tozeroy'
lines[key]["fillcolor"]=to_rgba(colors[key],kwargs['opacity'] if 'opacity' in kwargs else .3 )
if 'bar' in kind:
lines_plotly=[Bar(lines[key]) for key in keys]
else:
lines_plotly=[Scatter(lines[key]) for key in keys]
for trace in lines_plotly:
if isinstance(trace['name'],pd.tslib.Timestamp):
trace.update(name=str(trace['name']))
if bestfit:
if type(bestfit)==list:
keys=bestfit
d={}
for key in keys:
bestfit=df[key].bestfit()
d[bestfit.formula]=bestfit
bestfit_lines=pd.DataFrame(d).to_iplot(bestfit=False,colors=bestfit_colors,kind='scatter')
for line in bestfit_lines:
line['line']['dash']='dash'
if not bestfit_colors:
line['line']['color']=to_rgba(line['line']['color'],.6)
data=Data(lines_plotly)
data.extend(bestfit_lines)
return data
return Data(lines_plotly)
